MIMO (Multiple Input Multiple Output) technology using multiple antennas at both the transmitter and receiver sides has recently emerged as one of the most significant technical breakthroughs in modern communications. The original MIMO is known as D-BLAST (see G. J. Foschini, “Layered space-time architecture for wireless communication in a fading environment when using multielement antennas”, Bell Labs Tech. J., pp. 41-59, 1996.) and a more realistic strategy as V-BLAST (see G. D. Golden, J. G. Foschini, R. A. Valenzuela, and P. W. Wolniansky, “DETECTION ALGORITHM AND INITIAL LABORATORY RESULTS USING V-BLAST SPACE-TIME COMMUNICATION ARCHITECTURE,” Electron. Lett., vol. 35, pp. 14-15, January 1999) by nulling and canceling with reasonable tradeoff between complexity and performance.
The original MIMO spatial multiplexing was proposed for narrow band and flat-fading channels. In a multipath-fading channel, the orthogonality of the spreading codes is destroyed and the Multiple-Access-Interference (MAI) along with the Inter-Symbol-Interference (ISI) is introduced. With a very short spreading gain, the conventional Rake receiver could not provide acceptable performance. The LMMSE (Linear-Minimum-Mean-Square-Error)-based chip equalizer is promising to restore the orthogonality of the spreading code, so as to suppress both the ISI and MAI. However, the LMMSE equalizers involve the inverse of a large correlation matrix with the general complexity of O((NF)3), where N is the number of Rx antenna and F is the channel length. This is very expensive for hardware implementation.
Earlier, the chip equalizer problem was solved in either of the following frameworks:                (i) adaptive stochastic gradient algorithms such as LMS;        (ii) Conjugate Gradient algorithm; and        (iii) The FFT-based MIMO chip equalizer.The algorithms of option (i) suffer from stability problems because the convergence depends on the choice of good step size (see M. J. Heikkila, K. Ruotsalainen and J. Lilleberg, “SPACE-TIME EQUALIZATION USING CONJUGATE-GRADIENT ALGORITHM IN WCDMA DOWNLINK”, IEEE Proceeding in PIMRC, pp. 673-677, 2002). The algorithms of option (ii) exhibit complexity at the order of O((NF)2), according to Levinson and Shur. For option (iii), the FFT-based equalizer reduces the (NF×NF) matrix inverse to LF submatrices inverse of size (NXN) (see J. Zhang, T. Bhatt, G. Mandyam, “EFFICIENT LINEAR EQUALIZATION FOR HIGH DATA RATE DOWNLINK CDMA SIGNALING”, Proceeding of IEEE Asilomar Conference on Signals, Systems and Computers, 2003).        
The FFT-based fast algorithm noted above by Zhang, Bhatt and Mandyam uses a banded-Toeplitz structure of the correlation matrix. Although this FFT-based algorithm avoids the inverse of the original correlation matrix with the dimension of NF×NF, the inventors believe that some matrix inverse is inevitable for the MIMO receiver. For a MIMO receiver with high dimension, the complexity of a MIMO receiver increases dramatically with the number of antennas. The principle operation of interest is the architecture of many 4×4 matrix inverses in the frequency domain for the 1×4, 2×4 and 4×4 MIMO configurations or 1×2, 2×2 receivers with over sampling factor of 2. This is because these are seen to be the most likely deployed in the near future. The fact that the receiver must be embedded into a portable device makes the design of low complexity mobile receivers very critical for widespread commercial deployment of low cost products. For practical considerations, it is necessary to determine which range of possible matrix inverse architectures is most suitable for VLSI implementation.
What is needed in the art is a receiver architecture and corresponding method for reducing receiver complexity in a MIMO system while remaining within constraints imposed by portable wireless devices, mobile stations such as mobile telephones, PDAs with two-way communications, personal internet-access devices, and other such appliances.